High light and temperature reduce photosynthetic efficiency through different mechanisms in the C4 model Setaria viridis

Anderson, Cheyenne M.; Mattoon, Erin M.; Zhang, Ningning; Becker, Eric; McHargue, William; Yang, Jiani; Patel, Dhruv; Dautermann, Oliver; McAdam, Scott A. M.; Tarin, Tonantzin; Pathak, Sunita; Avenson, Tom J.; Berry, Jeffrey; Braud, Maxwell; Niyogi, Krishna K.; Wilson, Margaret; Nusinow, Dmitri A.; Vargas, Rodrigo; Czymmek, Kirk J.; Eveland, Andrea L.; Zhang, Ru

doi:10.1038/s42003-021-02576-2

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Published: 16 September 2021

High light and temperature reduce photosynthetic efficiency through different mechanisms in the C₄ model Setaria viridis

Communications Biology volume 4, Article number: 1092 (2021) Cite this article

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Abstract

C₄ plants frequently experience high light and high temperature conditions in the field, which reduce growth and yield. However, the mechanisms underlying these stress responses in C₄ plants have been under-explored, especially the coordination between mesophyll (M) and bundle sheath (BS) cells. We investigated how the C₄ model plant Setaria viridis responded to a four-hour high light or high temperature treatment at photosynthetic, transcriptomic, and ultrastructural levels. Although we observed a comparable reduction of photosynthetic efficiency in high light or high temperature treated leaves, detailed analysis of multi-level responses revealed important differences in key pathways and M/BS specificity responding to high light and high temperature. We provide a systematic analysis of high light and high temperature responses in S. viridis, reveal different acclimation strategies to these two stresses in C₄ plants, discover unique light/temperature responses in C₄ plants in comparison to C₃ plants, and identify potential targets to improve abiotic stress tolerance in C₄ crops.

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Introduction

Several of the world’s most economically important staple crops utilize C₄ photosynthesis, including Zea mays and Sorghum bicolor. C₄ photosynthesis concentrates CO₂ around Rubisco (ribulose-1,5-bisphosphate carboxylase/oxygenase) by employing biochemical reactions within mesophyll (M) and bundle sheath (BS) cells^1,2. The high local concentration of CO₂ near Rubisco favors carbon fixation over photorespiration, which is initiated by the oxygenase activity of Rubisco^1,3. C₄ photosynthesis is hypothesized to have been selected by low CO₂, high light (HL), and high temperature (HT) conditions^4,5. C₄ plants typically exhibit higher photosynthetic and water-use efficiencies than their C₃ counterparts under high light or high temperature⁶. However, C₄ crops experience more frequent, damaging high light or high temperature stresses in their natural environments than C₃ crops, with reduced C₄ crop yield regularly occurring in warmer regions⁷. As the mean global temperature continues to increase, maize yields are estimated to decrease between 4% and 12% for an increase of each degree Celsius⁷. Photosynthesis in maize leaves is inhibited at leaf temperatures above 38 °C. Recent data from 408 sorghum cultivars shows that breeding efforts over the last few decades have developed high-yielding sorghum cultivars with considerable variability in heat resilience and even the most heat-tolerant sorghum cultivars did not offer much resilience to warming temperatures, with a temperature threshold of 33 °C, beyond which sorghum yields start to decline⁸. Under natural conditions, especially at the tops of canopies, direct sunlight can be very intense and thus oversaturate the photosynthetic mechanism in C₄ plants. Sorghum leaves had reduced stomatal conductance and net CO₂ assimilation rates after 4 h exposure to high light mimicking nature sunlight⁹. To improve C₄ crop yields, it is crucial to holistically approach how C₄ plants respond to high light or high temperature, two of the most influential environmental factors that can compromise C₄ photosynthesis.

High light responses have been studied extensively in C₃ plants^{10,11,12,13,14,15}. To cope with reactive oxygen species (ROS) production and photooxidative stress resulting from high light, C₃ plants have evolved many protective mechanisms which act on different timescales^10,14. Non-photochemical quenching (NPQ), especially its predominant component, energy-dependent quenching (qE), acts within seconds to dissipate excess light energy as heat^10,16. The formation of qE depends on the thylakoid lumen pH, the photosystem II (PSII) polypeptide PsbS, and the accumulation of the xanthophyll pigment zeaxanthin^17,18,19. In C₃ plants, under high light, violaxanthin is converted to the intermediate pigment antheraxanthin which is then converted to zeaxanthin by the enzyme violaxanthin de-epoxidase²⁰. Accumulation of zeaxanthin is also necessary for the induction of a slower-relaxing component of NPQ, zeaxanthin-dependent quenching (qZ)²¹. State transitions, which restructure the light-harvesting complexes (LHCs) around PSII and PSI, occur on the order of minutes^10,16. When photoprotective processes are insufficient, high light can result in photoinhibition (qI), which takes hours to recover¹⁰. Following high light exposure, expansion of the thylakoid lumen, swelling of the grana margin, and de-stacking of the thylakoid grana facilitate PSII repair by promoting accessibility and repair of PSII machinery^15,22,23,24. High light stress also results in dynamic transcriptional regulation of photosynthetic genes and induces the abscisic acid (ABA) pathway in the C₃ model plant Arabidopsis thaliana (Arabidopsis throughout)¹¹.

High temperature is known to affect many cellular processes in C₃ plants, including various aspects of photosynthesis^{25,26,27,28,29}. C₃ plants under high temperature have shown decreases in photosynthetic rates, inactivation of Rubisco, reduction of plastoquinone (PQ), and increase in cyclic electron flow (CEF) around photosystem I (PSI)³⁰. Arabidopsis leaves treated with high temperature of 40 °C had increased plastoglobuli (PG) formation³¹. PG are thylakoid-associated plastid lipoprotein particles whose size, shape, and counts respond to abiotic stresses³². Additionally, high temperature induces the expression of heat shock transcription factors (HSFs), many of which have been implicated in transcriptional responses to numerous abiotic stresses, including high light and high temperature³³. The induced HSFs increase the expression of heat shock proteins (HSPs), which are chaperone proteins involved in proper protein folding in response to high temperature and other abiotic stresses³⁴.

Unlike C₃ plants, studies on how C₄ plants respond to high light or high temperature are largely limited, especially the underlying coordination between mesophyll and bundle sheath cells and the multi-level effects of high light and high temperature on photosynthesis, transcriptomes, and ultrastructure of C₄ plants. A recent study examined the effects of high light stress in the C₄ grass Setaria viridis over 4 days, with sampling points for photosynthetic parameters, sugar quantification, and transcriptome analyses every 24 h³⁵. They reported relatively minor transcriptional changes but a large accumulation of sugars without repression of photosynthesis in high-light-treated samples³⁵. These results suggest that leaves with prolonged high-light treatment undergo adaptive acclimation and transcriptional homeostasis in a few days. However, the short-term transcriptional responses of C₄ plants to high light remain largely unknown. In sorghum leaves, high light induced the avoidance response in mesophyll chloroplasts and the swelling of bundle sheath chloroplasts (by cross-section light microscope images), but the underlying mechanisms are unclear⁹. Research about how C₄ photosynthesis responds to high temperature is mainly limited to biochemical and gas exchange analyses which suggest that high temperature results in Rubisco activation³⁶, affects the activities of C₄ carbon fixation enzymes³⁷, and decreases the bundle sheath conductance while increases CO₂ leakiness^38,39. Two transcriptome analyses in maize under high temperature have been reported^40,41, but thorough analysis of C₄ transcriptome with multi-level effects under high temperature is rare. Additionally, ultrastructural analysis in C₄ plants under high light or high temperature can help us understand how these two stresses limits C₄ photosynthesis and affects the coordination between mesophyll and bundle sheath cells, but currently such information is lacking.

To gain deeper insights into the molecular and physiological responses of C₄ plants to high light or high temperature, we used the green foxtail Setaria viridis as a model. S. viridis is an excellent model to study C₄ photosynthesis because of its expanding genetics and genomics toolkit, relatively quick generation time (8~10 weeks, seed to seed), and similarity to agronomically important C₄ crops, e.g., maize and sorghum^2,42,43. We hypothesized that high light or high temperature affected C₄ plants at different levels and linking multi-level changes could improve our understanding of high light or high temperature tolerance in C₄ plants. We investigated the response of S. viridis to moderately high light or high temperature over a 4 h time course at photosynthetic, ultrastructural, and transcriptomic levels (Fig. 1a). We monitored the dynamic changes of transcriptomes, pigments, and ABA levels during the different treatments. We also measured photosynthetic parameters and ultrastructural changes after 4 h treatments, which revealed cumulative changes associated with the different treatments.

**Fig. 1: High light and high temperature resulted in a comparable reduction in net CO₂ assimilation rates and high light also caused significant photoinhibition in *S. viridis* leaves.**

Although we observed a comparable reduction in photosynthetic efficiency in high-light- or high-temperature-treated leaves, detailed analysis at multiple levels revealed different acclimation strategies to these two stresses in S. viridis. The transcriptional changes under high temperature were less extensive and more dynamic than under high light. We revealed different responses of mesophyll and bundle sheath cells under high temperature or high light. The high-light-treated leaves had over-accumulated starch in both mesophyll and bundle sheath chloroplasts, which may increase chloroplast crowdedness and inhibit PSII repair. While both high light and high temperature induced PG formation in chloroplasts, high-temperature-treated mesophyll chloroplasts also had swollen grana. Additionally, we demonstrated the crosstalk between high light response and ABA signaling in C₄ plants. Our research provides a systematic analysis of high light and high temperature responses in S. viridis and identifies potential targets to improve stress tolerance in C₄ crops.

Results

High light or high temperature caused a comparable reduction in photosynthesis and high light also resulted in photoinhibition

S. viridis leaves treated with 4 h high light (HL_4h) exhibited significantly reduced maximum efficiencies of PSII (F_v/F_m) as compared to those with 4 h control treatment (ctrl_4h) (Fig. 1b), suggesting high-light-induced photoinhibition. Net CO₂ assimilation rates (A_Net) were significantly reduced in high-light- or high-temperature-treated leaves in response to changes in light or CO₂ (Fig. 1c, d). Pre-treatment control leaves (ctrl_0h) also had lower A_Net as compared to ctrl_4h leaves, suggesting circadian regulation of photosynthesis over the course of the day. The comparisons between different treatments at the 4 h time point should exclude the effects of circadian regulation. Leaf temperature was stable at 31 °C under control and high light treatments while it increased gradually from 31 to 37 °C by the end of 4 h treatment of 40 °C (Supplementary Fig. 1). Stomatal conductance and transpiration rates in response to light were reduced in HL_4h leaves, especially at the beginning of the light response curve (Supplementary Fig. 2a, c). Stomatal conductance and transpiration rate in response to CO₂ were lower in HL_4h or HT_4h leaves than in ctrl_4h leaves (Supplementary Fig. 2b, d). PSII efficiency and electron transport rates in light-adapted leaves were reduced in HL_4h leaves as compared to ctrl_4h leaves in response to light (Supplementary Fig. 2e, g).

To estimate and model a variety of photosynthetic parameters, we assessed various aspects of leaf-level gas exchange measurements based on the light response curves and CO₂ response curves (Supplementary Fig. 3). High light or high temperature compromised photosynthetic capacities and reduced several photosynthetic parameters in HL_4h and HT_4h leaves compared to ctrl_4h leaves, including gross maximum CO₂ assimilation rates (A_max), maximum carboxylation rates (V_cmax), and quantum yields of CO₂ assimilation (Supplementary Fig. 3a–c). HL_4h leaves had reduced stomatal conductance (g_s) but increased light compensation point as compared to ctrl_4h leaves (Supplementary Fig. 3e, g). HT_4h leaves had reduced light saturation point as compared to ctrl_4h leaves (Supplementary Fig. 3h).

Transcriptomics revealed important differences in key pathways responding to high light or high temperature

To investigate the transcriptional patterns that may underlie the photosynthetic phenomena observed above, we performed RNA-seq analysis (Fig. 1a). Principal component analysis (PCA) of transcripts per million (TPM) (Supplementary Data 1) normalized read counts from control, high light, and high temperature treatments showed that the experimental conditions dominated the variance in the dataset (Fig. 2a).

**Fig. 2: Time-course transcriptome data reveal dynamic responses to high light or high temperature in *S. viridis*.**

Next, we compared differentially expressed genes (DEGs) between high light and high temperature treatments. Genes that were either up- or down-regulated in at least one time point were included in the lists of DEGs for each condition. Utilizing this method, we were able to broadly compare the trends between the high light and high temperature transcriptomes. There were more DEGs identified in the high light dataset than in the hightemperature dataset (Fig. 2b, Supplementary Table 1, and Supplementary Data 2). Significantly more genes were up- or down-regulated in both high-light- and high-temperature-treated transcriptomes than would be expected by random chance (Fig. 2b and Supplementary Data 4). Additionally, significantly more genes were regulated in opposite directions between high light and high temperature transcriptomes than would be expected by random chance. To visualize how DEGs were conserved between time points within treatments, we plotted the overlaps between up- and down-regulated genes at each time point. In high-light-treated samples, 742 genes were up-regulated at 1, 2, and 4 h time points, representing the largest subset of uniquely overlapping genes and the core high-light-induced genes (Fig. 2c and Supplementary Data 3). Similarly, 674 genes were down-regulated at all the three time points of high light treatment, representing the core high-light-reduced genes. Conversely, in the high-temperature-treated samples, the expression pattern was dominated by genes differentially expressed at a single time point (Fig. 2d), indicating that the transcriptional response to high temperature was more transient and dynamic than that to high light. In high-temperature-treated samples, 102 and 72 genes were up- and down-regulated at all the three time points, representing the core high-temperature-induced and -reduced genes, respectively.

To reveal transcriptional changes that may explain the reduced photosynthesis under high light or high temperature, we grouped DEGs into several key pathways. Investigation of genes related to the light reaction of photosynthesis revealed that many genes involved in PSII assembly/repair and photoprotection (e.g., PsbS) were up-regulated in high light, while many genes relating to LHCII and the core complexes of PSII/PSI were down-regulated in high light (Fig. 3a, b). Although high temperature treatment did not result in the same extent of differential regulation of light-reaction-related genes as high light, STN7, a kinase involved in state 1 to state 2 transitions⁴⁴ was induced, while TAP38, a phosphatase involved in state 2 to state 1 transitions⁴⁵ was repressed in high-temperature-treated leaves (Supplementary Fig. 4a). This suggests a possible heat-induced state transition to move the mobile LHCII from PSII (state 1) to PSI (state 2). Additionally, several genes related to the chloroplast NDH (NADPH dehydrogenase) complex were up-regulated in the high temperature treatment (Fig. 3b). Furthermore, when investigating genes involved in CEF (Supplementary Fig. 4), we found that key components of CEF, PGR5 (proton gradient regulation 5)⁴⁶ and two copies of PGRL1 (PGR5-like photosynthetic phenotype 1)⁴⁷, were induced under high temperature, suggesting heat-induced CEF around PSI.

**Fig. 3: High light differentially regulated genes involved in photosynthesis more than high temperature.**

Under high light treatment, the transcriptional changes of genes involved in the Calvin-Benson cycle were less extensive than those involved in the light reactions of photosynthesis (Fig. 3c). Rubisco activase (RCA) is essential for CO₂ fixation by maintaining the active status of Rubisco^48,49. The S. viridis genome has two adjacent genes encoding RCAs (Supplementary Fig. 5). Protein sequence alignment of the two S. viridis RCAs with Arabidopsis RCAs revealed one SvRCA-α that retains the two conserved redox-sensitive cysteine residues as in AtRCA_α, and one SvRCA_β that has a higher basal expression (approximately 700-fold higher) than SvRCA_α and possibly the major RCA in S. viridis. SvRCA_α was highly induced during the entire 4 h high temperature treatment (Fig. 3c).

Key genes involved in photorespiration, e.g., GOX1 (glycolate oxidase)^50,51 and AGT1 (Serine:glyoxylate aminotransferase)⁵² were down-regulated under high light (Fig. 3c). GOX1 and several other genes involved in photorespiration, PGLP1 (2-phosphoglycolate phosphatase)⁵³, HPR1 (hydroxypyruvate reductase)⁵⁴, and PLGG1 (plastidic glycolate/glycerate transporter)⁵⁵ were induced under high temperature, suggesting heat-induced photorespiration.

Some genes important for C₄ carbon metabolism were up-regulated under high light (Fig. 3c), e.g., PEPC_B (phosphoeynylpyruvate carboxylase) and NADP-MDH (NAD-dependent malate dehydrogenase)¹. Carbonic anhydrase⁵⁶ (CA_A) was induced under both high light and high temperature.

By investigating pathways associated with photosynthesis, we found high light increased the expression of starch biosynthesis/degradation genes and genes encoding PG-localized proteins (Fig. 4a), but down-regulated several genes in the sugar-sensing pathway (Fig. 4b) and differentially regulated several sugar transporter genes (Supplementary Fig. 4b). These transcriptional changes were much less pronounced under high temperature.

**Fig. 4: High light and high temperature differentially regulated genes involved in several key pathways.**

Several HSFs had highly induced expression under either high light or high temperature, but interestingly, different HSFs were up-regulated during these two stresses (Fig. 4c). HSFA6B was a notable exception, which was induced in both high light and high temperature. A set of shared HSPs were induced under both stresses, but the induction was quicker and stronger under high temperature than under high light, especially the small HSPs, suggesting shared and also temporally distinct transcriptional responses of HSPs under high light and high temperature.

We also investigated genes associated with ROS pathways (Supplementary Fig. 4c). Specialized ROS scavenging pathways have evolved in plants⁵⁷. We identified genes encoding antioxidant enzymes in S. viridis and investigated their expression patterns under high light or high temperature. Three gene families of antioxidant enzymes have many members with strong differential expression in high-light-treated leaves: TRX (thioredoxin), POX (peroxidases), and GST (glutathione S-transferase). Interestingly, within each of the three antioxidant pathways, some genes were up-regulated while others were down-regulated in high-light-treated leaves. A similar pattern was shown in high-temperature-treated leaves, although with fewer differentially regulated genes.

The reduced stomatal conductance in HL_4h leaves (Supplementary Fig. 2a) suggested there may be changes in ABA pathways and leaf ABA levels. Our RNA-seq analysis showed that several genes in the ABA pathways were up-regulated in response to high light (Fig. 5a). Additionally, ABA levels were increased 3-fold in HL_1h leaves followed by a return to baseline by HL_4h (Fig. 5b).

**Fig. 5: High light up-regulated genes involved in the abscisic acid (ABA) pathway and transiently increased leaf ABA levels.**

To distinguish mesophyll- and bundle sheath-specific transcriptomic responses and gain more information about how these two specialized cell types function together under high light or high temperature, we investigated the cell-type specificity of our pathways of interest (Supplementary Fig. 6 and Supplementary Data 6) using previously published mesophyll- and bundle sheath-specific transcriptomes under control conditions⁵⁸. We observed several cell-type-specific transcriptional responses to high light or high temperature, e.g., pathways related to ROS scavenging, sugar transport, and HSPs.

High light treatment induced NPQ in S. viridis

The increased photoinhibition and PsbS transcription in HL_4h leaves prompted us to quantify NPQ and xanthophyll pigments. NPQ was significantly higher in HL_4h leaves than in ctrl_4h leaves in response to light and CO₂ (Fig. 6a, b). The high-light-induced NPQ measured by LI-6800 was confirmed using MultispeQ with the estimated NPQ, NPQ_(T), based on a method that estimates NPQ in light-adapted leaves⁵⁹ (Supplementary Fig. 7c). The increased NPQ was also supported by the observed 4-fold increase of zeaxanthin (Fig. 6c) during high light. Additionally, high light treatment doubled the intermediate antheraxanthin level (Fig. 6d) and tripled the overall de-epoxidation state of the xanthophyll cycle (Fig. 6e). In Arabidopsis, lutein also has a role in NPQ or qE and can substitute for zeaxanthin in qE formation⁶⁰. Lutein as well as total carotenoids were significantly induced in HL_4h leaves (Supplementary Fig. 8c, d). These results indicate the occurrence of photoprotection in high-light-treated leaves. Control and high temperature treatments had little effect on leaf pigments.

**Fig. 6: High light induced non-photochemical quenching (NPQ) and increased zeaxanthin as well as de-epoxidation levels.**

High light or high temperature altered chloroplast ultrastructures

The reduced photosynthesis (Fig. 1c, d) in HL_4h and HT_4h leaves, and the high-light-induced photoinhibition (Fig. 1b) and transcripts related to the starch as well as PG pathways (Fig. 4a) led us to investigate the ultrastructural changes of the mesophyll and bundle sheath chloroplasts in ctrl_4h, HL_4h, and HT_4h leaves using transmission electron microscopy (TEM) (Supplementary Fig. 9). TEM images showed HL_4h leaves had increased relative starch volume fraction and chloroplast area in both mesophyll and bundle sheath chloroplasts, but decreased relative volume fractions of stroma plus stroma lamellae (unstacked thylakoid membranes) in mesophyll chloroplasts as compared to ctrl_4h leaves (Fig. 7 and Supplementary Table 2), suggesting increased starch accumulation and chloroplast crowdedness under high light. Starch quantification using biochemical assays confirmed 3x higher starch levels in HL_4h leaves as compared to ctrl_4h leaves (Fig. 7m). In HT_4h leaves, the relative starch volume fractions had a small increase in bundle sheath chloroplasts but decreased in mesophyll chloroplasts as compared to the control condition (Fig. 7 and Supplementary Table 2). Considering the small reduction of bundle sheath chloroplast area, the starch volume either had little change or slightly reduced as compared to the control, consistent with the starch quantification (Fig. 7m). High temperature did not affect the relative volume of stroma or stroma lamellae in either mesophyll or bundle sheath chloroplasts (Fig. 7i).

**Fig. 7: High light increased starch accumulation and both high light and high temperature treatments induced chloroplast plastoglobuli formation in *S. viridis* leaves.**

Like in other C₄ plants, S. viridis grana are predominantly present in the mesophyll chloroplasts. Bundle sheath chloroplasts also have some grana, which are absent from the central area but present in the peripheral region (Fig. 7d–f). High light reduced grana width in mesophyll chloroplasts and the relative volume, height, and area of grana in bundle sheath chloroplasts as compared to the control condition (Fig. 7j, Supplementary Fig. 10, and Supplementary Table 2). The high temperature effects on grana structure were quite different from high light. Mesophyll chloroplasts under high temperature had increased relative volume, height, area, and mean layer thickness of grana, indicating heat-induced grana swelling. However, in bundle sheath chloroplasts, high temperature decreased the relative volume, width, and area of grana, suggesting that high temperature affected the grana structure differently in mesophyll and bundle sheath chloroplasts.

High light increased PG count and the total PG area per chloroplast, while it decreased the mean individual PG size in mesophyll chloroplasts, indicating smaller but more numerous PGs in mesophyll chloroplasts (Fig. 7k, l and Supplementary Table 2). Furthermore, high light increased individual PG size and total PG area per chloroplast in bundle sheath chloroplasts (Supplementary Table 2). High temperature increased individual PG size and total PG area, suggesting heat-induced PG formation in both mesophyll and bundle sheath chloroplasts.

High-light- and high-temperature-treated leaves had reduced photosynthetic capacity

The over-accumulated starch in HL_4h leaves (Fig. 7) and the increased leaf ABA levels (Fig. 5) led us to investigate photosynthesis immediately after different treatments without dark-adaptation under simulated stress conditions in the LI-6800 leaf chamber (Fig. 8). Under the same temperature and light intensity in the LI-6800 leaf chamber, most photosynthetic parameters with or without dark-adaptation were similar (groups 1 vs. 2) (Fig. 8). Under the simulated treatment condition in the LI-6800 leaf chamber (group 3), HL_4h leaves had higher net CO₂ assimilation rates (A_Net) and stomatal conductance (g_s) under 600 µmol photons m⁻² s⁻¹ light than ctrl_4h leaves under 200 µmol photons m⁻² s⁻¹ light, but both parameters in HL_4h leaves were lower than those in ctrl_4h leaves under the same light intensity (groups 3 and 4) (Fig. 8a). This suggests that HL_4h leaves had reduced capacities for A_Net and g_s as compared ctrl_4h leaves under the same condition. Under the simulated treatment condition (group 3), HL_4h leaves under 600 µmol photons m⁻² s⁻¹ light had reduced PSII operating efficiency (Fig. 8c), increased electron transport rates (Fig. 8d), and increased NPQ (Fig. 8f) as compared to the ctrl_4h leaves under 200 µmol photons m⁻² s⁻¹ light, consistent with light-induced electron transport and NPQ.

**Fig. 8: High-light- or high-temperature-treated leaves had lower photosynthetic capacities than leaves treated with the control condition.**

Without dark-adaptation, HT_4h leaves had similar A_Net as ctrl_4h leaves (Fig. 8a, group 2). This may be due to the transient recovery of photosynthesis after switching the HT_4h leaves from 40 °C in the growth chamber to 25 °C in the LI-6800 leaf chamber for measurements. Under the same light intensity, HT_4h leaves had significantly lower A_Net (Fig. 8a) and more reduced plastoquinone (Fig. 8e) than ctrl_4h leaves. Under the simulated treatment condition in LI-6800 leaf chamber (group 3), HT_4h leaves had increased stomatal conductance (Fig. 8b) but reduced A_Net as compared to ctrl_4h leaves (Fig. 8a), consistent with transpiration cooling of leaf temperature (Supplementary Fig. 1) and reduced photosynthetic capacity in high-temperature-treated leaves (Supplementary Fig. 3a–c).

The activity of ATP synthase was inhibited in high-light-treated leaves

Based on the high-light-induced starch accumulation, we hypothesized that starch may inhibit photosynthesis through feedback regulation. We measured electrochromic shift (ECS) and chlorophyll fluorescence using MultispeQ⁶¹ to evaluate proton fluxes and the transthylakoid proton motive force (pmf) in vivo^62,63,64. Different treatments did not significantly change pmf (Fig. 9a). HL_4h leaves had significantly reduced proton conductivity and lower proton flux rates as compared to ctrl_4h leaves (Fig. 9b, c), indicating reduced ATP synthase activity in high-light-treated leaves. The MultispeQ NPQ_(T) data showed that the high-light-induced NPQ was more sensitive to pmf than ctrl_4h leaves, with higher NPQ produced at a given level of proton motive force in HL_4h leaves than in ctrl_4h leaves (Fig. 9d).

**Fig. 9: High light treatment inhibited ATP synthase activity.**

Discussion

We investigated how the C₄ model plant S. viridis responds to high light or high temperature stresses at photosynthetic, transcriptomic, and ultrastructural levels (Fig. 1a) and revealed limitations of photosynthesis under these two stresses. The high light (900 µmol photons m⁻² s⁻¹) and high temperature (40 °C) treatments we chose were both moderate stresses within the physiological range for S. viridis. Although the impact of moderate stresses can be difficult to analyze due to mild phenotypes, moderate stresses are highly relevant and occur frequently in the field⁶⁵. Understanding the impacts of moderate stresses on C₄ plants is imperative for agricultural research. The moderately high light and high temperature we used reduced net CO₂ assimilation rates at comparable levels in S. viridis leaves (Fig. 1c), but via different mechanisms (Fig. 10).

**Fig. 10: Summary of how *S. viridis* responds to high light or high temperature.**

Starch over-accumulation may contribute to photoinhibition in high-light-treated leaves

In response to high light, S. viridis induced NPQ to dissipate excess light energy via increased PsbS transcription and zeaxanthin accumulation (Figs. 3a and 6c). At the transcriptional level, high-light-treated plants up-regulated transcripts involved in PSII assembly/repair and photoprotection before down-regulating transcripts involved in LHCII, PSII core complex, and PSI complex (Fig. 3), suggesting a strategy to dissipate light and repair damaged PSII before the remodeling of photosystems. With the rapid induction of photoprotective pathways, it was initially surprising to see the significant amount of photoinhibition in high-light-treated leaves of S. viridis (Fig. 1b), but the high-light-induced starch accumulation may provide some insight.

Our TEM data showed that the mean relative starch volume fraction was increased significantly in both mesophyll and bundle sheath chloroplasts in HL_4h leaves as compared to ctrl_4h leaves (Fig. 7 and Supplementary Table 2). The increased starch accumulation likely resulted from increased CO₂ fixation rates (Fig. 8a) but imbalance of starch synthesis/ degradation and sugar transport from downstream pathways under high light. In C₃ plants, starch is mostly present in mesophyll chloroplasts where photosynthesis occurs^66,67. In C₄ plants, starch is present in both bundle sheath and mesophyll chloroplasts (Fig. 7a–f), although Rubisco predominantly localizes in the bundle sheath chloroplasts⁶⁷. The over-accumulated starch increased the crowdedness of the chloroplasts (Fig. 7 and Supplementary Table 2), which may hinder PSII repair, especially in mesophyll chloroplasts where PSII is enriched. PSII complexes are concentrated in the stacked grana regions; during PSII repair, damaged PSII subunits migrate from the stacked grana region to the grana margin and the unstacked grana region (stroma lamellae) where the proteins involved in PSII repair are localized (e.g., FtsH, Deg proteases that degrade damaged PSII subunits)^15,68. In Arabidopsis under high light, the grana lumen and margin swell to facilitate protein diffusion and PSII repair^23,69, however, we did not see these changes in high-light-treated S. viridis leaves (Supplementary Fig. 10d, e, i). Starch over-accumulation and increased chloroplast crowdedness may slow down the migration of damaged PSII subunits and inhibit PSII repair, contributing to the high-light-induced photoinhibition (Figs. 1b and 10). Additionally, ATP synthase activity was significantly reduced in HL_4h leaves as compared to ctrl_4h leaves (Fig. 9b, c), which may be associated with the starch accumulation and sugar feedback inhibition of photosynthesis. High-light-treated Arabidopsis plants had reduced starch in chloroplasts⁷⁰, which may reflect the differences in experimental conditions or the stronger capability to use high light for carbon fixation in C₄ plants than in C₃ plants.

High light differentially regulated genes involved in sugar-sensing pathways

Sugar signaling integrates sugar production with environmental cues to regulate photosynthesis^35,71,72. In C₃ plants, some of the sugar-sensing pathways include: (1) SnRK1 pathway (sucrose-non-fermenting 1-related protein kinase 1, starvation sensor, active under stressful and sugar deprivation conditions to suppress growth and promote survival)^73,74,75; and (2) Trehalose pathway (trehalose is a signal metabolite in plants under abiotic stresses and helps plants survive stresses)^65,76. In the trehalose pathway, trehalose-6-phosphate synthase (TPS) produces trehalose-6-phosphate (T6P); the T6P phosphatase (TPP) dephosphorylates T6P to generate trehalose⁶⁵. T6P correlates with sucrose levels, inhibits SnRK1 pathway, and primes gene expression for growth in response to sucrose accumualtion^77,78. Sugar-sensing pathways under abiotic stresses are under-explored in C₄ plants³⁵. Research in maize showed potential inhibition of the SnRK1 pathway by T6P in reproductive tissues (e.g., kernels) under drought and salt stresses, but their roles and interaction in leaves are unclear^79,80. Our RNA-seq data showed that two subunits of SnRK1 (β2, γ4) were highly down-regulated under high light (Fig. 4b), suggesting possible inhibition of the SnRK1 pathway. A copy of the potential catalytically active TPS (TPSI) in S. viridis was induced and two copies of TTP were down-regulated during high light (Fig. 4b), suggesting possible increased level of T6P. Based on the expression pattern of genes involved in sugar-sensing pathways and the over-accumulated starch under high light, we postulated that high-light-treated S. viridis leaves had increased sugar levels, and possibly up-regulated T6P sugar-sensing pathway to down-regulate the SnRK1 pathway and promote plant growth, which may alleviate the stress of starch over-accumulation and photosynthesis inhibition under high light.

Potential links between high light response and ABA pathway exist in S. viridis

The links between high light responses and ABA have been reported in C₃ plants^11,12,81,82. Arabidopsis ABA biosynthesis mutants (e.g., nced3) were more sensitive to high light than WT^11,12. High-light-treated S. viridis leaves had reduced capacity for stomatal conductance (Fig. 8b), which can most likely be attributed to an acute increase of ABA levels in high-light-treated leaves (Fig. 5b). Although ABA levels were only significantly increased at HL_1h and then gradually decreased, the ABA-induced stomatal closure may be prolonged. Consistent with this, RNA-seq data showed increased expression of genes involved in ABA responses and signaling during the 4 h high light treatment (Fig. 5a). Stomatal conductance increases with light to increase CO₂ uptake, which also increases water loss. To reduce water loss and improve water-use efficiency, a relatively lower stomatal conductance under high light may be an adaptive response. Our results in S. viridis provide insight into the reduced stomatal conductance and photosynthesis in sorghum leaves under high light⁹.

ABA homeostasis is maintained by the balance of its biosynthesis, catabolism, reversible glycosylation, and transport pathways¹⁹. Several ABA biosynthesis genes were up-regulated during high light (Fig. 5a), including NCED1 (9-cis epoxycarotenoid dioxygenase)^19,83,84 and ABA1/ZEP1, suggesting that local, de novo ABA biosynthesis may be one source of the rapid and large induction of ABA at HL_1h. The up-regulation of CYP707As, which are responsible for ABA degradation⁸⁵, may contribute to the gradual reduction of ABA levels after 1 h high light. Furthermore, the S. viridis homolog of Arabidopsis BG1 (glucosidase, hydrolyzes inactive ABA-GE to active ABA in endoplasmic reticulum)⁸⁶ was induced at HL_2h and HL_4h. Dehydration rapidly induces polymerization of AtBG1 and a 4-fold increase in its enzymatic activity⁸⁶. It is possible that the hydrolysis of ABA-GE to ABA by polymerized BG1 may precede the induction of the BG1 transcript, contributing to the transiently increased ABA levels. Several putative ABA transporters were not differentially expressed (Supplementary Data 6), but a S. viridis homolog of the Arabidopsis ABA importer ABCG40 was down-regulated in high light (Fig. 5a), suggesting ABA import from other parts of the plant to leaves may be less likely. Thus, the high light increased ABA level may be due to ABA de novo biosynthesis and/or reversible glycosylation from ABA-GE to ABA.

High temperature responses had distinct features in comparison to high light

Compared to high light, HT_4h leaves showed much less change in starch accumulation, little change in chloroplast crowdedness (Fig. 7), and no photoinhibition (Fig. 1). Grana dimension increased in high-temperature-treated mesophyll chloroplasts (Supplementary Table 2), suggesting heat-induced grana swelling. In contrast, bundle sheath chloroplasts have slightly increased starch, no change of chloroplast area, but decreased grana dimension under high temperature, suggesting cell-type-specific heat responses. PG formation was highly induced in both mesophyll and bundle sheath chloroplasts under high temperature, which may be associated with heat-increased thylakoid membrane leakiness, consistent with previous reports^26,87,88. Induced grana swelling and PG formation may reflect heat-induced damage to chloroplast ultrastructure, which may contribute to the reduced photosynthetic rates under high temperature.

The transcriptome changes under high temperature were less extensive but more dynamic than under high light (Figs. 2–5). High temperature induced more PG formation than high light (Supplementary Table 2), however, surprisingly there were few transcriptional changes of genes encoding proteins that localize to PG under high temperature (Fig. 4a). These results suggest the heat-induced PG formation may be a direct and physical response of thylakoid membranes to moderately high temperature and not regulated at the transcriptional level.

Response to high temperature also showed some unique transcriptional changes that were absent or minimal under high light. First, high temperature resulted in high and sustained induction of Rubisco activase (RCA-α) (Fig. 3c). RCA removes inhibitors from Rubisco, maintains Rubisco activation, and is important for carbon fixation^48,49. Rubisco is thermostable but RCAs are heat labile, resulting in reduced Rubisco activation and CO₂ fixation under HT³⁶. Plants grown in warm environments usually have RCAs that are more thermotolerant^89,90,91. In S. viridis, maize, and sorghum, high temperature induces the protein level of RCA_α and the rate of RCA_α induction is associated with the recovery rate of Rubisco activation and photosynthesis⁹². Our results, taken with previously published reports, suggest the heat-induced RCA_α may be the thermotolerant isoform. Understanding the function and regulation of RCAs may help improve thermotolerance of photosynthesis in C₄ plants. Additionally, high temperature up-regulated small HSPs much quicker than high light.

Key genes involved in photorespiration (Fig. 3c) and CEF around PSI (Supplementary Fig. 4a) were up-regulated under high temperature, suggesting high-temperature-induced photorespiration and CEF. C₄ plants employ carbon-concentrating mechanisms (CCM) to concentrate CO₂ around Rubisco and reduce photorespiration in bundle sheath chloroplasts. However, S. viridis bundle sheath chloroplasts have a small number of grana (Fig. 7d–f), where PSII is present and can be a source of O₂ production. Photorespiration increases with temperature faster than photosynthesis^30,93 and high temperature may also increase the CO₂ leakiness of bundle sheath chloroplasts^38,39, promoting photorespiration and reducing photosynthesis. CEF generates only ATP without NADPH, balances the ATP/NADPH ratio, generates transthylakoid proton motive force (pmf), and protects both PSI and PSII from photo-oxidative damage in C₃ plants^94,95. Increased CEF activity has been frequently reported under various stressful conditions in C₃ plants^26,96,97 and in S. viridis under salt stress⁹⁸, indicating its important role in stress protection. To compensate for the extra ATP needed for the CCM, C₄ plants are proposed to have high CEF in bundle sheath chloroplasts^3,99. Heat-induced CEF could protect photosynthesis under high temperature by maintaining transthylakoid pmf and generating extra ATP.

Although high light and high temperature responses had their own unique features, their transcriptional responses had significant overlaps (Fig. 2b). We identified 42 highly induced genes (FC ≥ 5) and 13 highly repressed genes (FC ≤ −5) in both conditions (Supplementary Table 1 and Supplementary Data 5). The 42 highly induced genes provide potential targets for improving resistance to high light and high temperature in C₄ crops, including several putative transcription factors, HSP20/70/90 family proteins, β-amylase, and a putative aquaporin transporter for promoting CO₂ conductivity in C₄ plants^3,100,101. Additionally, HSFA6B was induced (2 ≤ FC ≤ 5) under both high light and high temperature. HSFA6B reportedly operates as a downstream regulator of the ABA-mediated stress response and is involved in thermotolerance in Arabidopsis, wheat, and barley^102,103. This gene may be involved in regulation of genes that are common to both the high light and high temperature responses and it would be interesting for further study to generate high-light- and high-temperature-tolerant C₄ crops. Frey et al. identified 39 heat-tolerance genes in maize that were significantly associated with heat tolerance and up-regulated in most of the 8 maize inbred lines⁴¹. Five S. viridis homologs of the maize heat-tolerance genes were also up-regulated in our RNA-seq data under high temperature, providing potential engineering targets to improve heat tolerance in C₄ plants (Supplementary Data 5). More potential gene targets to improve high light and/or high temperature tolerance in S. viridis and other C₄ crops are included in Supplementary Data 5.

The different responses in mesophyll and bundle sheath chloroplasts in S. viridis are particularly interesting and warrant further study. We sorted high-light or high-temperature-induced DEGs into mesophyll- and bundle sheath-specific pathways based on previously published cell-type-specific transcriptomes⁵⁸ (Supplementary Fig. 6). Although we cannot rule out some transcripts may have altered cell-type specificity under stressful conditions, due to the functional specificity of the mesophyll and bundle sheath cells, a significant fraction of the mesophyll- and bundle sheath-specific transcripts likely keep similar cell-type specificity under our high light and high temperature conditions as compared to the published control condition. Our analysis revealed mesophyll- and bundle sheath-specific transcriptional regulation in response to high light or high temperature in S. viridis. Under high light, the majority of mesophyll-specific DEGs related to ROS scavenging and HSPs were up-regulated while the majority of bundle sheath-specific DEGs related to these two pathways were down-regulated, suggesting mesophyll cells may require more ROS scavenging and HSPs than bundle sheath cells in response to high light, likely due to more ROS production and higher need for maintaining protein homeostasis in mesophyll cells than in bundle sheath cells under high light. In contrast, under high temperature, many ROS-scavenging DEGs were up-regulated in bundle sheath cells but down-regulated in mesophyll cells (possibly due to heat-induced photorespiration) while DEGs related to HSPs were up-regulated in both cell types. It is intriguing that high light up-regulated mesophyll-specific sugar transporters but down-regulated bundle sheath-specific sugar transporters. In Arabidopsis, SWEET16/17 plays a key role in facilitating bidirectional sugar transport along sugar gradient across the tonoplast of vacuoles^104,105. The homolog of SWEET16/17 in S. viridis is mesophyll cell specific and was up-regulated in high light (Supplementary Fig. 4b), suggesting SvSWEET16/17 may mediate sugar uptake into vacuoles in response to a high concentration of cytosolic sugar level in mesophyll cells. The down-regulation of bundle sheath-specific SWEETs under high light may indicate feedback inhibition of phloem sugar loading due to unmatched sugar usage in downstream processes¹⁰⁶.

In comparison to the C₃ model plant Arabidopsis, the C₄ model plant S. viridis has shared and unique responses under high light and high temperature. The shared responses include induced NPQ, PsbS transcription, zeaxanthin accumulation, PG formation, and ABA levels under high light, and the induced PG formation under high temperature. The unique responses in S. viridis to high light include the over-accumulated starch in both mesophyll and bundle sheath chloroplasts and increased chloroplast crowdedness. In high temperature, the unique responses in S. viridis include dynamic transcriptome regulation and different heat responses of mesophyll and bundle sheath chloroplasts. Additionally, S. viridis has M/BS cell-type-specific transcriptional responses to high light or high temperature. The reduced photosynthetic capacity in S. viridis leaves under high light or high temperature also demonstrated the need to improve the tolerance to these two stresses in C₄ plants.

In summary, we elucidated how the C₄ model plant S. viridis responds to moderately high light or high temperature at the photosynthetic, transcriptomic, and ultrastructural levels (Supplementary Table 3). Our research furthers understanding of how C₄ plants respond to high light and high temperature by linking the data from multiple levels, reveals different acclimation strategies to these two stresses in C₄ plants, discovers unique high light/temperature responses in C₄ plants in comparison to C₃, demonstrates M/BS cell-type specificity under these two stresses, distinguishes adaptive from maladaptive responses, and identifies potential targets to improve abiotic stress tolerance in C₄ crops.

Methods

Plant growth conditions and treatments

S. viridis ME034 (also known as ME034v) plants were grown in a controlled environmental chamber under constant 31 °C, 50% humidity, ambient CO₂ conditions, 12/12 h day/night, and leaf-level light intensity of 250 μmol photons m⁻² s⁻¹. Similar level of growth light has been used frequently in literature for S. viridis under control conditions^{58,98,107,108}. Seeds were germinated on Jolly Gardener C/V Growing Mix (BGF Supply Company, Oldcastle, OCL50050041) and fertilized with Jack’s 15-5-15 (BGF Supply Company, J.R. Peters Inc., JRP77940) with an Electrical Conductivity (EC) of 1.4. At 7 days after sowing (DAS), seedlings were transplanted to 3.14″ × 3.18″ × 3.27″ pots. At 13 DAS, 4 h after light was on in the growth chamber, plants with fourth fully expanded true leaves were selected for 4 h high light (leaf-level light intensity of 900 μmol photons m⁻² s⁻¹ and chamber temperature of 31 °C) or 4 h high temperature (chamber temperature of 40 °C and leaf-level light intensity of 250 μmol photons m⁻² s⁻¹) treatments carried out in separate controlled environmental chambers under 50% humidity and ambient CO₂ conditions. A separate set of plants remained in the control growth condition.

Gas exchange and chlorophyll fluorescence measurements

Leaf-level gas exchange and pulsed amplitude modulated (PAM) chlorophyll a fluorescence were measured using a portable gas-exchange system LI-6800 coupled with a Fluorometer head 6800-01 A (LI-COR Biosciences, Lincoln, NE). Fourth, fully expanded, intact true leaves of S. viridis plants from different treatments were first dark-adapted for 20 min in the LI-6800 chamber to measure maximum PSII efficiency (F_v/F_m) under constant CO₂ partial pressure of 400 ppm in the sample cell, leaf temperature 25 °C, leaf VPD 1.5 kPa, fan speed 10,000 RPM, and flow rate 500 μmol s⁻¹. We then performed the light response curves followed by CO₂ response curves (A/c_i curve) as described (Supplementary Table 4). Red-blue actinic light (90%/10%) and 3–6 biological replicates for each treatment were used for all measurements. We used a leaf temperature of 25 °C for light and CO₂ response curves as described in previous publications for S. viridis regardless of growth temperatures^{56,98,109,110,111}. During all measurements, the instrument parameters were consistent and stable. For CO₂ response curves, all net CO₂ assimilation rates were corrected with the empty chamber data to account for inevitable and minor LI-6800 leaf chamber leakiness during the CO₂ response curves following the established protocols¹¹².

Photosynthetic parameters were calculated as described⁶² (see formulas, Supplementary Table 5). To estimate the true NPQ, F_m used in the NPQ formula (F_m/F_mF_m′ – 1) needs to be the maximum chlorophyll fluorescence in fully relaxed, dark-adapted leaves in which there is no quenching^62,113. F_m and F_mF_m′ are the maximum chlorophyll fluorescence yields in dark-adapted and light-adapted leaves, respectively^62,113,114. In control leaves, F_m could be reached with 20 min dark-adaptation without further change after that, but high-light-treated leaves needed a much longer recovery period to relax the quenching processes due to the light-induced photoinhibition (Supplementary Fig. 7a). Because the values of F_m in dark-adapted ctrl_4h leaves were highly consistent among different biological replicates and reflected the reference level of F_m (i.e., without stress treatments), we used the mean F_m of ctrl_4h leaves as a baseline to calculate NPQ in leaves with different treatments.

To investigate photosynthetic performance in plants immediately following 4 h of different treatments (control, high light or high temperature), we also performed short LI-6800 measurements for 5 min on each plant immediately after 4 h treatments without dark-adaptation at 400 ppm CO₂ with indicated leaf temperatures and light intensities (Fig. 8). To estimate photosynthetic parameters under different treatments as in the growth chambers, the LI-6800 leaf chamber was set to simulate the condition of different treatments: control (31 °C, 200 µmol photons m⁻² s⁻¹ light), high light (31 °C, 600 µmol photons m⁻² s⁻¹ light,) or high temperature (40 °C, 200 µmol photons m⁻² s⁻¹ light). The temperature and light refer to the conditions in the LI-6800 leaf chamber. The light in LI-6800 leaf chamber (90% red and 10% blue) was different from the white light in our growth chambers, therefore we selected two lights (200 and 600 µmol photons m⁻² s⁻¹) in the LI-6800 leaf chamber that were close to the white lights in growth chambers based on the light quantification in the red (580–670 nm) and blue (440-540 nm) spectrum range. LI-6800 light intensities of 200 and 600 µmol photons m⁻² s⁻¹ were also two of the conditions used in the light response curves with dark-adaptation (Figs. 1c and 8, group 1), allowing for direct comparison. Individual plants were used for each replicate.

The high abundance of PSI in bundle sheath chloroplasts of C₄ leaves can affect chlorophyll fluorescence measurement (up to 50%) and underestimate the PSII efficiency (F_v/F_m) and electron transport rates^115,116. Thus, our chlorophyll fluorescence data were corrected with 0.5 F_o¹¹⁶. F_o is the mean minimal chlorophyll fluorescence in dark-adapted leaves under the control condition (ctrl_4h). The PSII operating efficiency calculated from the corrected and uncorrected chlorophyll fluorescence data correlated with each other but the corrected data yielded higher PSII efficiency, with the maximum PSII efficiency in ctrl_4h leaves closer to the theoretical values of 0.86¹¹⁷ (Fig. 1b).

Modeling of photosynthetic parameters using leaf-level gas-exchange information

To model photosynthetic parameters, we used gas-exchange data from light response curves and CO₂ response curves (A/c_i curves). The model parameterization and analyses were conducted in R 3.4.3 Project software^® (R Development Core Team 2016). First, light response curves were fitted as previously described¹¹⁸. We fit a non-linear least squares regression (non-rectangular hyperbola) to estimate photosynthetic parameters (Supplementary Fig. 3). A/c_i curves were fitted as previously described¹¹⁹ to estimate the V_cmax (the maximum rate of carboxylation). We used the C₄ photosynthesis model using a Bayesian analysis approach as described in Feng et al. (2013)¹²⁰. The normality of the data was verified with the Shapiro-Wilk test. Statistical analysis was performed using Student’s two-tailed t-test with unequal variance by comparing ctrl_4h with all other conditions.

RNA isolation

To isolate RNA from leaves, four biological replicates containing two 2-cm middle leaf segments from two plants for each time point and treatment were collected from fourth fully expanded true leaves into screw cap tubes (USA Scientific, 1420-9700) with a grinding bead (Advanced Materials, 4039GM-S050) and immediately frozen in liquid nitrogen and stored at −80 °C. Frozen samples were homogenized using a paint shaker. RNA was extracted using a Trizol method with all centrifugation at 4 °C and 11,000 RCF. First, 1 mL of Trizol Reagent (Invitrogen, 15596018) was added to homogenized leaf tissue and resuspended, then 200 µL of Chloroform:Isoamyl alcohol (25:1) was added and vortexed. Tubes were centrifuged for 15 min, and 600 µL from the aqueous layer was transferred to a clean tube with equal volume Chloroform:Isoamyl alcohol, vortexed, and centrifuged for 5 min. Next, 450 µL of aqueous layer was transferred to 0.7x volume 100% Isopropanol, mixed well, and chilled for 30 min in −20 °C freezer. Samples were centrifuged for 15 min to pellet RNA. Supernatant was decanted, and RNA pellet was rinsed twice with ice-cold 75% ethanol with a 2 min centrifugation following each rinse. RNA was dried in a laminar flow hood until residual ethanol evaporated and was resuspended in 50 µL of nuclease-free H₂O. RNA was quantified using a NanoDrop and Qubit RNA Broad Range (BR) Assay Kit (Thermo Fisher Scientific Inc., Q10210) with the Qubit 3.0 machine. RNA integrity was verified using a Bioanalyzer Nano Assay (Genome Technology Access Center, Washington University in St Louis).

RNA-seq library construction and sequencing

RNA samples were diluted to 200 ng/µL in nuclease-free H₂O for a total of 1 µg RNA. Libraries were generated with the Quantseq 3′ mRNA-seq library prep kit FWD for Illumina (Lexogen, 015.96). Libraries were generated according to manufacturer’s instructions. Cycle count for library amplification for 1 µg mRNA was tested using the PCR add-on kit for Illumina (Lexogen, 020.96). qPCR was performed and a cycle count of 13 was determined for the amplification of all libraries. For library amplification, the Lexogen i5 6 nt Dual Indexing Add-on Kit (5001-5004) (Lexogen, 047.4 × 96) was used in addition to the standard kit to allow all libraries to have a unique combination of i5 and i7 indices. All libraries were quantified using Qubit dsDNA High Sensitivity (HS) Assay Kit (Thermo Fisher Scientific Inc., Q32854) with the Qubit 3.0 machine. Prepared libraries were pooled to equimolar concentrations based on Qubit assay reads. Pooled libraries were submitted to Novogene to be sequenced on the HiSeq4000 platform (Illumina) with paired end, 150 bp reads.

Mapping and transcript quantification

Single-end reads were trimmed and quality-checked using Trim Galore (version 0.6.2). Trimmed reads from each library were mapped and processed for transcript quantification using Salmon (version 1.1.0) in quasi-mapping mode with a transcriptome index built from the S. viridis transcript and genome files (Sviridis_311_v2; Phytozome v12.1, sequence data produced by the US Department of Energy Joint Genome Institute and the S. viridis Genome Sequencing Project)⁴². Salmon outputs were imported into R using the Bioconductor package tximport (1.16.0) to extract gene-level expression values represented by transcript per million (TPM) for each gene across every time point, tissue, and treatment group sampled. PCA was performed with TPM normalized read counts of all genes using the R package FactoMineR¹²¹.

Differential expression analysis

Genes that met minimum read count cutoffs of at least 10 raw reads in at least 10% of samples (14,302 genes) were included in differential expression analysis using DeSeq2, FDR < 0.05¹²². High light or high temperature treatment time points were compared to the control condition from the same time point. DEGs between different time points in either high light or high temperature were visualized in UpSetR¹²³. To identify genes in key pathways of interest in S. viridis, we used the MapMan annotations for the closely related S. italica (RRID:SCR_003543). From the S. italica MapMan annotations, we identified the best hit in S. viridis for genes in pathways of interest. We then manually curated these lists based on relevant literature to obtain genes in pathways of interest (Supplementary Data 6), as well as to provide further annotation information for genes identified using the MapMan annotations. We sorted the differentially expressed genes in pathways of interest into fold change (FC) bins based on their DeSeq2 fold change values and presented their expression patterns. FC bins were defined as follows: highly induced: FC ≥ 5; moderately induced: 5 > FC ≥ 2; slightly induced: 2 > FC > 0; not differentially expressed: FC = 0; slightly repressed: 0 > FC > −2; moderately repressed: −2 ≥ FC > −5; highly repressed: FC ≤ −5. Heatmaps of pathways of interest were generated using the R package pheatmap (version 1.0.12. https://CRAN.R-project.org/package=pheatmap).

ABA quantification

Leaf samples of three biological replicates were harvested at 0, 1, 2, and 4 h of control, high light, or high temperature treatment. The fresh leaf weight was immediately measured after harvesting. The samples were quickly placed in liquid nitrogen and then stored in −80 °C freezer until further processing. Frozen leaf tissue was homogenized and 15 ng of [²H₆]-abscisic acid was added as an internal standard. Samples were dried to completeness under vacuum. ABA was resuspended in 200 µL of 2% acetic acid in water (v/v) and then centrifuged; an aliquot was then taken for quantification. Foliar ABA levels were quantified by liquid chromatography tandem mass spectrometry with an added internal standard using an Agilent 6400 Series Triple Quadrupole liquid chromatograph associated with a tandem mass spectrometer according to the previously described methods¹²⁴.

Pigment analysis

Three biological replicates of one 2 cm middle leaf segment were collected from fourth fully expanded true leaves into screw cap tubes (USA Scientific, 1420-9700) with a grinding bead (Advanced Materials, 4039GM-S050), immediately frozen in liquid nitrogen, and stored at −80 °C. During pigment extraction, 600 µL ice-cold acetone were added to the samples before they were homogenized in a FastPrep-24 5G (MP Biomedicals) at 6.5 m s⁻¹ for 30 s at room temperature. Cell debris were removed by centrifugation at 21,000g for 1 min. The supernatant was filtered through a 4 mm nylon glass syringe prefilter with 0.45 µm pore size (Thermo Scientific) and analyzed by HPLC. HPLC analyses were performed on an Agilent 1100 separation module equipped with a G1315B diode array and a G1231A fluorescence detector; data were collected and analyzed using Agilent LC Open Lab ChemStation software. Pigment extracts were separated on a ProntoSIL 200-5 C30, 5.0 μm, 250 mm × 4.6 mm column equipped with a ProntoSIL 200-5-C30, 5.0 μm, 20 mm × 4.0 mm guard column (Bischoff Analysentechnik) and gradient conditions as previously described¹²⁵. Assuming interconversion of the intermediate antheraxanthin between both zeaxanthin and violaxanthin, the de-epoxidation level can be calculated by (zeaxanthin + 0.5 antheraxanthin) / (violaxanthin + antheraxanthin + zeaxanthin)¹²⁶.

Transmission electron microscopy (TEM)

S. viridis leaves were collected after 4 h of different treatments and prepared for TEM. Four-millimeter biopsy punches were taken from the middle leaf segments of the fourth fully expanded leaves and fixed for 2 h in 2% paraformaldehyde and 2% glutaraldehyde (EM Science, Hatfield, PA, USA) plus 0.1% Tween20 in 0.1 M sodium cacodylate at pH 7.4 at room temperature and then at 4 °C overnight. Samples were then rinsed 3x in buffer and fixed in 2% osmium tetroxide (EM Science, Hatfield, PA, USA) in ELGA water for 2 h, rinsed 3x in ELGA water and placed in 1% uranyl acetate in ELGA water at 4 °C overnight and then at 50 °C for 2 h. Next, samples were rinsed 5x in water, dehydrated in a graded acetone series and embedded in Epon-Araldite (Embed 812, EM Science, Hatfield, PA, USA). Embedments were trimmed and mounted in the vise-chuck of a Leica Ultracut UCT ultramicrotome (Leica, Buffalo Grove, IL, USA). Ultrathin sections (~60 to 70 nm) were cut using a diamond knife (type ultra 35 °C; Diatome), mounted on copper grids (FCFT300-CU-50, VWR, Radnor, PA, USA), and counterstained with lead citrate for 8 min²⁵. Samples were imaged with a LEO 912 AB Energy Filter Transmission Electron Microscope (Zeiss, Oberkochen, Germany). Micrographs were acquired with iTEM software (ver. 5.2) (Olympus Soft Imaging Solutions GmbH, Germany) with a TRS 2048 × 2048k slow-scan charge-coupled device (CCD) camera (TRÖNDLE Restlichtverstärkersysteme, Germany). Ninety electron micrographs were quantified for each experimental treatment using image analysis (FIJI software, National Institutes of Health) and stereology (Stereology Analyzer version 4.3.3, ADCIS, France). Each TEM image was acquired at 8,000X magnification and 1.37 nm pixel resolution with arrays of up to 5 × 5 tiles using automated Multiple Image Alignment software module (settings: correlation = 1, FFT algorithm, overlap area = linear weighted, movement = emphasize, and equalize). TEM images were analyzed with Stereology Analyzer software version 4.3.3 to quantify relative volume of various cell parameters including stroma, stroma lamellae, starch granules, and grana within individual chloroplasts (Supplementary Fig. 9b). Grid type was set as “point” with a sampling step of 500 × 500 pixels and pattern size of 15 × 15 pixels. The percent of relative volume for each parameter was collected after identifying all grid points within one chloroplast and further analyzed in excel. TEM images with a magnification of 8 K were used in the Fiji (ImageJ) analysis. The images were scaled to 0.7299 pixel nm⁻¹ in ImageJ before analyzing the chloroplast area, plastoglobuli area, and grana dimensions. The height of grana margin (positions 1 and 3) and grana core (position 2) were quantified as described previously²³ (Supplementary Fig. 10d, e). The “polygon selections” tool was used to quantify the chloroplast and plastoglobuli area by outlining the target structure. The individual plastoglobuli (PG) size was measured using ImageJ. All PG in a chloroplast were quantified to get the total PG area per chloroplast. The “straight” tool was used to quantify grana height and width. The grana number and PG number were counted manually. Choosing the correct statistical test to reflect the quantified data is essential in making conclusions. Three different statistical tests were used to find the significance of p-values. The negative binomial test was used for counting data that followed a negative binomial distribution. The Kolmogorov-Smirnov test was used for relative volume data since it is commonly used to find significance between data in a form of ratios. A two-tailed t-test with unequal variance was used for all other data that followed a normal distribution. All three statistical tests compared the treatment conditions to the control conditions of the same cell type. Each treatment had three biological replicates and a total of 90~120 images of each treatment were analyzed.

Starch quantification

To isolate starch from leaves, three biological replicates of 2 cm middle leaf segments were collected from fourth fully expanded true leaves into screw cap tubes (USA Scientific, 1420-9700) with a grinding bead (Advanced Materials, 4039GM-S050) and immediately frozen in liquid nitrogen and stored at −80 °C. Frozen samples were homogenized using a paint shaker. For starch quantification, leaves decolorized by 80% ethanol and starch concentration was subsequently measured using a starch assay kit (Megazyme, K-TSTA-100A).

MultispeQ measurement

A MultispeQ⁶¹ v2.0 was used to measure chlorophyll fluorescence parameters and ECS in S. viridis leaves at the start or after 4 h treatments of control, high light, or high temperature. ECS results from light–dark-transition-induced electric field effects on carotenoid absorbance bands^62,127 and is a useful tool to monitor proton fluxes and the transthylakoid proton motive force (pmf) in vivo^63,64. Light drives photosynthetic electron transport along the thylakoid membrane and proton fluxes across the thylakoid membrane. Protons flux into the thylakoid through H₂O oxidation at PSII and plastoquinol oxidation at cytochrome b₆f complex; protons flux out of the thylakoid mainly through ATP synthase to make ATP, which is driven by the transthylakoid pmf^63,64. The total amplitude of ECS signal during the light–dark transition, ECS_t, represents the transthylakoid pmf. The decay time constant of light–dark-transition-induced ECS signal, τ_ECS, is inversely proportional to proton conductivity (ɡ_H⁺ = 1/τ_ECS), which is proportional to the aggregate conductivity (or permeability) of the thylakoid membrane to protons and largely dependent on the activity of ATP synthase⁶². The proton flux rates, v_H+, calculated by ECS_t/τ_ECS, is the initial decay rate of the ECS signal during the light–dark transition and reflects the rate of proton translocation by the entire electron transfer chain, usually predominantly through the ATP synthase⁶². ECS was measured using MultispeQ and the dark interval relaxation kinetics with a modified Photosynthesis RIDES protocol at light intensities of 250, 500, and 1000 µmol photons m⁻² s⁻¹. The MultispeQ v2.0 was modified with a light guide mask to improve measurements on smaller leaves. Parameters at the different light intensities were measured sequentially on the middle segment of a fourth fully expanded true leaf at room temperature with no dark adaptation prior to measurements. The estimated NPQ, NPQ_(T), was measured by MultispeQ based on a method that does not require a dark-adapted state of the leaf for determination of F_m⁵⁹. NPQ_(T) uses the minimal fluorescence (F_o′) and maximal fluorescence (F_m′) in light-adapted leaves to estimate NPQ⁵⁹. Statistical significance was assigned with a two-tailed t-test assuming unequal variance.

Statistics and reproducibility

All data presented had at least three biological replicates. Detailed information about statistical analysis were described for each method above.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The datasets analyzed in this paper are included in this published article and supplementary information files. The RNA-seq data discussed in this publication was deposited in NCBI’s Gene Expression Omnibus (GEO)¹²⁸ and are accessible through GEO Series accession number GSE178320. Other information is available from the corresponding author on reasonable request.

References

Wang, L., Peterson, R. B. & Brutnell, T. P. Regulatory mechanisms underlying C₄ photosynthesis: Tansley review. New Phytol. 190, 9–20 (2011).
Article PubMed CAS Google Scholar
Huang, P., Shyu, C., Coelho, C. P., Cao, Y. & Brutnell, T. P. Setaria viridis as a model system to advance millet genetics and genomics. Front. Plant Sci. 7, 1781 (2016).
von Caemmerer, S. & Furbank, R. T. Strategies for improving C₄ photosynthesis. Curr. Opin. Plant Biol. 31, 125–134 (2016).
Article CAS Google Scholar
Sage, R. F. The evolution of C₄ photosynthesis. New Phytol. 161, 341–370 (2004).
Article PubMed CAS Google Scholar
Blätke, M.-A. & Bräutigam, A. Evolution of C₄ photosynthesis predicted by constraint-based modelling. eLife 8, e49305 (2019).
Article PubMed PubMed Central Google Scholar
Yamori, W., Hikosaka, K. & Way, D. A. Temperature response of photosynthesis in C₃, C₄, and CAM plants: temperature acclimation and temperature adaptation. Photosynth. Res. 119, 101–117 (2014).
Article PubMed CAS Google Scholar
Zhao, C. et al. Temperature increase reduces global yields of major crops in four independent estimates. Proc. Natl Acad. Sci. USA 114, 9326–9331 (2017).
Article PubMed PubMed Central CAS Google Scholar
Tack, J., Lingenfelser, J. & Jagadish, S. V. K. Disaggregating sorghum yield reductions under warming scenarios exposes narrow genetic diversity in US breeding programs. Proc. Natl Acad. Ssi. USA 114, 9296–9301 (2017).
Article CAS Google Scholar
Maai, E., Nishimura, K., Takisawa, R. & Nakazaki, T. Light stress-induced chloroplast movement and midday depression of photosynthesis in sorghum leaves. Plant Prod. Sci. 23, 172–181 (2020).
Article CAS Google Scholar
Dietz, K.-J. Efficient high light acclimation involves rapid processes at multiple mechanistic levels. J. Exp. Bot. 66, 2401–2414 (2015).
Article PubMed CAS Google Scholar
Huang, J., Zhao, X. & Chory, J. The Arabidopsis transcriptome responds specifically and dynamically to high light stress. Cell Rep. 29, 4186–4199.e3 (2019) .
Article PubMed PubMed Central CAS Google Scholar
Galvez-Valdivieso, G. et al. The high light response in Arabidopsis involves ABA signaling between vascular and bundle sheath cells. Plant Cell 21, 2143–2162 (2009).
Article PubMed PubMed Central CAS Google Scholar
Gollan, P. J. & Aro, E.-M. Photosynthetic signalling during high light stress and recovery: targets and dynamics. Philos. Trans. R. Soc. Lond. B Biol. Sci. 375, 20190406 (2020).
Article PubMed PubMed Central CAS Google Scholar
Takahashi, S. & Badger, M. R. Photoprotection in plants: a new light on photosystem II damage. Trends Plant Sci. 16, 53–60 (2011).
Kirchhoff, H. Structural changes of the thylakoid membrane network induced by high light stress in plant chloroplasts. Philos. Trans. R. Soc. Lond. B Biol. Sci. 369, 20130225 (2014).
Article PubMed PubMed Central CAS Google Scholar
Rochaix, J.-D. Regulation and dynamics of the light-harvesting system. Annu. Rev. Plant Biol. 65, 287–309 (2014).
Article PubMed CAS Google Scholar
Müller, P., Li, X.-P. & Niyogi, K. K. Non-photochemical quenching. A response to excess light energy. Plant Physiol. 125, 1558–1566 (2001).
Article PubMed PubMed Central Google Scholar
Murchie, E. H. & Ruban, A. V. Dynamic non‐photochemical quenching in plants: from molecular mechanism to productivity. Plant J. 101, 885–896 (2020).
Article PubMed CAS Google Scholar
Ma, Y. et al. Molecular mechanism for the regulation of ABA homeostasis during plant development and stress responses. Int. J. Mol. Sci. 19, 3643 (2018).
Article PubMed Central CAS Google Scholar
Jahns, P., Latowski, D. & Strzalka, K. Mechanism and regulation of the violaxanthin cycle: the role of antenna proteins and membrane lipids. Biochim. Biophys. Acta Bioenerg. 1787, 3–14 (2009).
Article CAS Google Scholar
Nilkens, M. et al. Identification of a slowly inducible zeaxanthin-dependent component of non-photochemical quenching of chlorophyll fluorescence generated under steady-state conditions in Arabidopsis. Biochim. Biophys. Acta 1797, 466–475 (2010).
Article PubMed CAS Google Scholar
Herbstová, M., Tietz, S., Kinzel, C., Turkina, M. V. & Kirchhoff, H. Architectural switch in plant photosynthetic membranes induced by light stress. Proc. Natl Acad. Sci. USA 109, 20130–20135 (2012).
Article PubMed PubMed Central Google Scholar
Yoshioka-Nishimura, M. et al. Quality control of photosystem II: direct imaging of the changes in the thylakoid structure and distribution of FtsH proteases in spinach chloroplasts under light stress. Plant Cell Physiol. 55, 1255–1265 (2014).
Article PubMed CAS Google Scholar
Flannery, S. E. et al. Developmental acclimation of the thylakoid proteome to light intensity in Arabidopsis. Plant J. 105, 223–244 (2020).
Schroda, M., Hemme, D. & Mühlhaus, T. The Chlamydomonas heat stress response. Plant J. 82, 466–480 (2015).
Article PubMed CAS Google Scholar
Zhang, R. & Sharkey, T. D. Photosynthetic electron transport and proton flux under moderate heat stress. Photosynth. Res. 100, 29–43 (2009).
Article PubMed CAS Google Scholar
Janni, M. et al. Molecular and genetic bases of heat stress responses in crop plants and breeding for increased resilience and productivity. J. Exp. Bot. 71, 3780–3802 (2020).
Article PubMed PubMed Central CAS Google Scholar
Qu, A.-L., Ding, Y.-F., Jiang, Q. & Zhu, C. Molecular mechanisms of the plant heat stress response. Biochem. Biophys. Res. Commun. 432, 203–207 (2013).
Article PubMed CAS Google Scholar
Kotak, S. et al. Complexity of the heat stress response in plants. Curr. Opin. Plant Biol. 10, 310–316 (2007).
Article PubMed CAS Google Scholar
Sharkey, T. D. Effects of moderate heat stress on photosynthesis: importance of thylakoid reactions, Rubisco deactivation, reactive oxygen species, and thermotolerance provided by isoprene. Plant Cell Environ. 28, 269–277 (2005).
Article CAS Google Scholar
Zhang, R., Wise, R. R., Struck, K. R. & Sharkey, T. D. Moderate heat stress of Arabidopsis thaliana leaves causes chloroplast swelling and plastoglobule formation. Photosynth. Res. 105, 123–134 (2010).
Article PubMed CAS Google Scholar
van Wijk, K. J. & Kessler, F. Plastoglobuli: plastid microcompartments with Integrated functions in metabolism, plastid developmental transitions, and environmental adaptation. Annu. Rev. Plant Biol. 68, 253–289 (2017).
Article PubMed CAS Google Scholar
Scharf, K.-D., Berberich, T., Ebersberger, I. & Nover, L. The plant heat stress transcription factor (Hsf) family: structure, function and evolution. Biochim. Biophys. Acta 1819, 104–119 (2012).
Article PubMed CAS Google Scholar
Al-Whaibi, M. H. Plant heat-shock proteins: a mini review. J. King Saud Univ. Sci. 23, 139–150 (2011).
Article Google Scholar
Henry, C. et al. Sugar sensing responses to low and high light in leaves of the C₄ model grass Setaria viridis. J. Exp. Bot. 71, 1039–1052 (2020).
PubMed CAS Google Scholar
Crafts-Brandner, S. J. & Salvucci, M. E. Sensitivity of photosynthesis in a C₄ plant, maize, to heat stress. Plant Physiol. 129, 1773–1780 (2002).
Article PubMed PubMed Central CAS Google Scholar
Boyd, R. A., Gandin, A. & Cousins, A. B. Temperature responses of C₄ photosynthesis: biochemical analysis of Rubisco, phosphoenolpyruvate carboxylase, and carbonic anhydrase in Setaria viridis. Plant Physiol. 169, 1850–1861 (2015).
PubMed PubMed Central CAS Google Scholar
Sonawane, B. V., Sharwood, R. E., von Caemmerer, S., Whitney, S. M. & Ghannoum, O. Short-term thermal photosynthetic responses of C₄ grasses are independent of the biochemical subtype. J. Exp. Bot. 68, 5583–5597 (2017).
Article PubMed PubMed Central CAS Google Scholar
Yin, X., van der Putten, P. E. L., Driever, S. M. & Struik, P. C. Temperature response of bundle-sheath conductance in maize leaves. J. Exp. Bot. 67, 2699–2714 (2016).
Article PubMed PubMed Central CAS Google Scholar
Shi, J., Yan, B., Lou, X., Ma, H. & Ruan, S. Comparative transcriptome analysis reveals the transcriptional alterations in heat-resistant and heat-sensitive sweet maize (Zea mays L.) varieties under heat stress. BMC Plant Biol. 17, 26 (2017).
Article PubMed PubMed Central CAS Google Scholar
Frey, F. P., Urbany, C., Hüttel, B., Reinhardt, R. & Stich, B. Genome-wide expression profiling and phenotypic evaluation of European maize inbreds at seedling stage in response to heat stress. BMC Genomics 16, 123 (2015).
Article PubMed PubMed Central CAS Google Scholar
Mamidi, S. et al. A genome resource for green millet Setaria viridis enables discovery of agronomically valuable loci. Nat. Biotechnol. 38, 1203–1210 (2020).
Article PubMed PubMed Central CAS Google Scholar
Thielen, P. M. et al. Reference genome for the highly transformable Setaria viridis ME034V. G3: Genes Genom. Genet. 10, 3467–3478 (2020).
Article CAS Google Scholar
Bellafiore, S., Barneche, F., Peltier, G. & Rochaix, J.-D. State transitions and light adaptation require chloroplast thylakoid protein kinase STN7. Nature 433, 892–895 (2005).
Article PubMed CAS Google Scholar
Pribil, M., Pesaresi, P., Hertle, A., Barbato, R. & Leister, D. Role of plastid protein phosphatase TAP38 in LHCII dephosphorylation and thylakoid electron flow. PLoS Biol. 8, e1000288 (2010).
Article PubMed PubMed Central CAS Google Scholar
Rantala, S. et al. PGR5 and NDH-1 systems do not function as protective electron acceptors but mitigate the consequences of PSI inhibition. Biochim. Biophys. Acta Bioenerg. 1861, 148154 (2020).
Article PubMed CAS Google Scholar
Hertle, A. P. et al. PGRL1 Is the elusive ferredoxin-plastoquinone reductase in photosynthetic cyclic electron flow. Mol. Cell 49, 511–523 (2013).
Article PubMed CAS Google Scholar
Bhat, J. Y., Thieulin-Pardo, G., Hartl, F. U. & Hayer-Hartl, M. Rubisco activases: AAA+ chaperones adapted to enzyme repair. Front. Mol. Biosci. 4, 20 (2017).
Mueller-Cajar, O. The diverse AAA+ machines that repair inhibited Rubisco active sites. Front. Mol. Biosci. 4, 31 (2017).
Article PubMed PubMed Central CAS Google Scholar
Dellero, Y. et al. Decreased glycolate oxidase activity leads to altered carbon allocation and leaf senescence after a transfer from high CO₂ to ambient air in Arabidopsis thaliana. J. Exp. Bot. 67, 3149–3163 (2016).
Article PubMed CAS Google Scholar
Kerchev, P. et al. Lack of GLYCOLATE OXIDASE1, but not GLYCOLATE OXIDASE2, attenuates the photorespiratory phenotype of CATALASE2-deficient Arabidopsis. Plant Physiol. 171, 1704–1719 (2016).
Article PubMed PubMed Central CAS Google Scholar
Modde, K. et al. High serine:glyoxylate aminotransferase activity lowers leaf daytime serine levels, inducing the phosphoserine pathway in Arabidopsis. J. Exp. Bot. 68, 643–656 (2017).
PubMed CAS Google Scholar
Schwarte, S. & Bauwe, H. Identification of the photorespiratory 2-phosphoglycolate phosphatase, PGLP1, in Arabidopsis. Plant Physiol. 144, 1580–1586 (2007).
Article PubMed PubMed Central CAS Google Scholar
Liu, Y., Guérard, F., Hodges, M. & Jossier, M. Phosphomimetic T335D mutation of hydroxypyruvate reductase 1 modifies cofactor specificity and impacts Arabidopsis growth in air. Plant Physiol. 183, 194–205 (2020).
Article PubMed PubMed Central CAS Google Scholar
Walker, B. J., South, P. F. & Ort, D. R. Physiological evidence for plasticity in glycolate/glycerate transport during photorespiration. Photosynth. Res. 129, 93–103 (2016).
Article PubMed PubMed Central CAS Google Scholar
Osborn, H. L. et al. Effects of reduced carbonic anhydrase activity on CO₂ assimilation rates in Setaria viridis: a transgenic analysis. J. Exp. Bot. 68, 299–310 (2017).
Article PubMed CAS Google Scholar
Hasanuzzaman, M. et al. Reactive oxygen species and antioxidant defense in plants under abiotic stress: revisiting the crucial role of a universal defense regulator. Antioxidants 9, 681 (2020).
Article PubMed Central CAS Google Scholar
John, C. R., Smith-Unna, R. D., Woodfield, H., Covshoff, S. & Hibberd, J. M. Evolutionary convergence of cell-specific gene expression in independent lineages of C₄ grasses. Plant Physiol. 165, 62–75 (2014).
Article PubMed PubMed Central CAS Google Scholar
Tietz, S., Hall, C. C., Cruz, J. A. & Kramer, D. M. NPQ _(T): a chlorophyll fluorescence parameter for rapid estimation and imaging of non-photochemical quenching of excitons in photosystem-II-associated antenna complexes: new, rapid probe of non-photochemical quenching. Plant Cell Environ. 40, 1243–1255 (2017).
Article PubMed CAS Google Scholar
Li, Z. et al. Lutein accumulation in the absence of zeaxanthin restores nonphotochemical quenching in the Arabidopsis thaliana npq1 mutant. Plant Cell 21, 1798–1812 (2009).
Article PubMed PubMed Central CAS Google Scholar
Kuhlgert, S. et al. MultispeQ Beta: a tool for large-scale plant phenotyping connected to the open PhotosynQ network. R. Soc. Open Sci. 3, 160592 (2016).
Article PubMed PubMed Central Google Scholar
Baker, N. R., Harbinson, J. & Kramer, D. M. Determining the limitations and regulation of photosynthetic energy transduction in leaves. Plant Cell Environ. 30, 1107–1125 (2007).
Article PubMed CAS Google Scholar
Kramer, D. M., Avenson, T. J. & Edwards, G. E. Dynamic flexibility in the light reactions of photosynthesis governed by both electron and proton transfer reactions. Trends Plant Sci. 9, 349–357 (2004).
Article PubMed CAS Google Scholar
Cruz, J. A. Plasticity in light reactions of photosynthesis for energy production and photoprotection. J. Exp. Bot. 56, 395–406 (2004).
Article PubMed CAS Google Scholar
Delorge, I., Janiak, M., Carpentier, S. & Van Dijck, P. Fine tuning of trehalose biosynthesis and hydrolysis as novel tools for the generation of abiotic stress tolerant plants. Front. Plant Sci. 5, 147 (2014).
Skryhan, K., Gurrieri, L., Sparla, F., Trost, P. & Blennow, A. Redox regulation of starch metabolism. Front. Plant Sci. 9, 1344 (2018).
Article PubMed PubMed Central Google Scholar
Weise, S. E., van Wijk, K. J. & Sharkey, T. D. The role of transitory starch in C₃, CAM, and C₄ metabolism and opportunities for engineering leaf starch accumulation. J. Exp. Bot. 62, 3109–3118 (2011).
Article PubMed CAS Google Scholar
Järvi, S., Suorsa, M. & Aro, E.-M. Photosystem II repair in plant chloroplasts—regulation, assisting proteins and shared components with photosystem II biogenesis. Biochim. Biophys. Acta Bioenerg. 1847, 900–909 (2015).
Article CAS Google Scholar
Puthiyaveetil, S. et al. Compartmentalization of the protein repair machinery in photosynthetic membranes. Proc. Natl Acad. Sci. USA 111, 15839–15844 (2014).
Article PubMed PubMed Central CAS Google Scholar
Balfagón, D. et al. Jasmonic acid Is required for plant acclimation to a combination of high light and heat stress. Plant Physiol. 181, 1668–1682 (2019).
Article PubMed PubMed Central CAS Google Scholar
Jang, J. C. & Sheen, J. Sugar sensing in higher plants. Plant Cell 6, 1665–1679 (1994).
PubMed PubMed Central CAS Google Scholar
Lastdrager, J., Hanson, J. & Smeekens, S. Sugar signals and the control of plant growth and development. J. Exp. Bot. 65, 799–807, (2014).
Tomé, F. et al. The low energy signaling network. Front. Plant Sci. 5, 353 (2014).
Li, L. & Sheen, J. Dynamic and diverse sugar signaling. Curr. Opin. Plant Biol. 33, 116–125 (2016).
Article PubMed PubMed Central CAS Google Scholar
Baena-González, E. & Hanson, J. Shaping plant development through the SnRK1–TOR metabolic regulators. Curr. Opin. Plant Biol. 35, 152–157 (2017).
Article PubMed CAS Google Scholar
Lunn, J. E., Delorge, I., Figueroa, C. M., Van Dijck, P. & Stitt, M. Trehalose metabolism in plants. Plant J. 79, 544–567 (2014).
Article PubMed CAS Google Scholar
Baena-González, E. & Lunn, J. E. SnRK1 and trehalose 6-phosphate—two ancient pathways converge to regulate plant metabolism and growth. Curr. Opin. Plant Biol. 55, 52–59 (2020).
Article PubMed CAS Google Scholar
Nunes, C. et al. The trehalose 6-phosphate/SnRK1 signaling pathway primes growth recovery following relief of sink limitation. Plant Physiol. 162, 1720–1732 (2013).
Article PubMed PubMed Central CAS Google Scholar
Henry, C. et al. Differential role for trehalose metabolism in salt-stressed maize. Plant Physiol. 169, 1072–1089 (2015).
Article PubMed PubMed Central CAS Google Scholar
Bledsoe, S. W. et al. The role of Tre6P and SnRK1 in maize early kernel development and events leading to stress-induced kernel abortion. BMC Plant Biol. 17, 74 (2017).
Article PubMed PubMed Central CAS Google Scholar
Fryer, M. J. et al. Control of Ascorbate Peroxidase 2 expression by hydrogen peroxide and leaf water status during excess light stress reveals a functional organisation of Arabidopsis leaves. Plant J. 33, 691–705 (2003).
Article PubMed CAS Google Scholar
Staneloni, R. J., Rodriguez-Batiller, M. J. & Casal, J. J. Abscisic acid, high-light, and oxidative stress down-regulate a photosynthetic gene via a promoter motif not involved in phytochrome-mediated transcriptional regulation. Mol. Plant 1, 75–83 (2008).
Article PubMed CAS Google Scholar
Endo, A. et al. Drought induction of Arabidopsis 9-cis-epoxycarotenoid dioxygenase occurs in vascular parenchyma cells. Plant Physiol. 147, 1984–1993 (2008).
Article PubMed PubMed Central CAS Google Scholar
Tan, B.-C. et al. Molecular characterization of the Arabidopsis 9-cis epoxycarotenoid dioxygenase gene family. Plant J. 35, 44–56 (2003).
Article PubMed CAS Google Scholar
Saito, S. et al. Arabidopsis CYP707As encode (+)-abscisic acid 8′-hydroxylase, a key enzyme in the oxidative catabolism of abscisic acid. Plant Physiol. 134, 1439–1449 (2004).
Article PubMed PubMed Central CAS Google Scholar
Lee, K. H. et al. Activation of glucosidase via stress-induced polymerization rapidly increases active pools of abscisic acid. Cell 126, 1109–1120 (2006).
Article PubMed CAS Google Scholar
Bukhov, N. G., Wiese, C., Neimanis, S. & Heber, U. Heat sensitivity of chloroplasts and leaves: leakage of protons from thylakoids and reversible activation of cyclic electron transport. Photosynth. Res. 59, 81–93 (1999).
Article CAS Google Scholar
Schrader, S. M., Wise, R., Wacholtz, W., ORT, D. & Sharkey, T. Thylakoid membrane responses to moderately high leaf temperature in Pima cotton. Plant Cell Environ. 27, 725–735 (2004).
Article CAS Google Scholar
Shivhare, D. & Mueller-Cajar, O. In vitro characterization of thermostable CAM Rubisco activase reveals a Rubisco interacting surface loop. Plant Physiol. 174, 1505–1516 (2017).
Article PubMed PubMed Central CAS Google Scholar
Wang, D. et al. Two Rubisco activase isoforms may play different roles in photosynthetic heat acclimation in the rice plant. Physiol. Plant. 139, 55–67 (2010).
Article PubMed CAS Google Scholar
Scafaro, A. P., Haynes, P. A. & Atwell, B. J. Physiological and molecular changes in Oryza meridionalis Ng., a heat-tolerant species of wild rice. J. Exp. Bot. 61, 191–202 (2010).
Article PubMed CAS Google Scholar
Kim, S. Y., Slattery, R. A. & Ort, D. R. A role for differential Rubisco activase isoform expression in C₄ bioenergy grasses at high temperature. GCB Bioenergy 13, 211–223 (2020).
Article CAS Google Scholar
Schuster, W. S. & Monson, R. K. An examination of the advantages of C₃–C₄ intermediate photosynthesis in warm environments. Plant Cell Environ. 13, 903–912 (1990).
Article Google Scholar
Yamori, W. & Shikanai, T. Physiological functions of cyclic electron transport around photosystem I in sustaining photosynthesis and plant growth. Annu. Rev. Plant Biol. 67, 81–106 (2016).
Article PubMed CAS Google Scholar
Johnson, G. N. Physiology of PSI cyclic electron transport in higher plants. Biochim. Biophys. Acta Bioenerg. 1807, 384–389 (2011).
Article CAS Google Scholar
He, Y. et al. Increasing cyclic electron flow is related to Na+ sequestration into vacuoles for salt tolerance in soybean. J. Exp. Bot. 66, 6877–6889 (2015).
Article PubMed PubMed Central CAS Google Scholar
Huang, W., Yang, S.-J., Zhang, S.-B., Zhang, J.-L. & Cao, K.-F. Cyclic electron flow plays an important role in photoprotection for the resurrection plant Paraboearufescens under drought stress. Planta 235, 819–828 (2012).
Article PubMed CAS Google Scholar
Essemine, J. et al. Photosynthetic and transcriptomic responses of two C₄ grass species with different NaCl tolerance. J. Plant Physiol. 253, 153244 (2020).
Article PubMed CAS Google Scholar
Nakamura, N., Iwano, M., Havaux, M., Yokota, A. & Munekage, Y. N. Promotion of cyclic electron transport around photosystem I during the evolution of NADP-malic enzyme-type C₄ photosynthesis in the genus Flaveria. New Phytol. 199, 832–842 (2013).
Article PubMed CAS Google Scholar
Kaldenhoff, R. Mechanisms underlying CO₂ diffusion in leaves. Curr. Opin. Plant Biol. 15, 276–281 (2012).
Article PubMed CAS Google Scholar
Weber, A. P. & von Caemmerer, S. Plastid transport and metabolism of C₃ and C₄ plants—comparative analysis and possible biotechnological exploitation. Curr. Opin. Plant Biol. 13, 256–264 (2010).
Article CAS Google Scholar
Huang, Y.-C., Niu, C.-Y., Yang, C.-R. & Jinn, T.-L. The heat stress factor HSFA6b connects ABA signaling and ABA-mediated heat responses. Plant Physiol. 172, 1182–1199 (2016).
PubMed PubMed Central CAS Google Scholar
Poonia, A. K. et al. Overexpression of wheat transcription factor (TaHsfA6b) provides thermotolerance in barley. Planta 252, 53 (2020).
Article PubMed CAS Google Scholar
Guo, W.-J. et al. SWEET17, a facilitative transporter, mediates fructose transport across the tonoplast of Arabidopsis roots and leaves. Plant Physiol. 164, 777–789 (2014).
Article PubMed CAS Google Scholar
Eom, J.-S. et al. SWEETs, transporters for intracellular and intercellular sugar translocation. Curr. Opin. Plant Biol. 25, 53–62 (2015).
Article PubMed CAS Google Scholar
Julius, B. T., Leach, K. A., Tran, T. M., Mertz, R. A. & Braun, D. M. Sugar transporters in plants: new insights and discoveries. Plant Cell Physiol. 58, 1442–1460 (2017).
Article PubMed CAS Google Scholar
Ermakova, M., Lopez-Calcagno, P. E., Raines, C. A., Furbank, R. T. & von Caemmerer, S. Overexpression of the Rieske FeS protein of the cytochrome b₆f complex increases C₄ photosynthesis in Setaria viridis. Commun. Biol. 2, 314 (2019).
Article PubMed PubMed Central CAS Google Scholar
Feldman, M. J. et al. Components of water use efficiency have unique genetic signatures in the model C₄ grass Setaria. Plant Physiol. 178, 699–715 (2018).
Article PubMed PubMed Central CAS Google Scholar
Ubierna, N., Gandin, A. & Cousins, A. B. The response of mesophyll conductance to short-term variation in CO₂ in the C₄ plants Setaria viridis and Zea mays. J. Exp. Bot. 69, 1159–1170 (2018).
Article PubMed PubMed Central CAS Google Scholar
Cano, F. J., Sharwood, R. E., Cousins, A. B. & Ghannoum, O. The role of leaf width and conductances to CO₂ in determining water use efficiency in C₄ grasses. New Phytol. 223, 1280–1295 (2019).
Article PubMed CAS Google Scholar
Danila, F. R., Quick, W. P., White, R. G., Caemmerer, Svon & Furbank, R. T. Response of plasmodesmata formation in leaves of C₄ grasses to growth irradiance. Plant Cell Environ. 42, 2482–2494 (2019).
Article PubMed CAS Google Scholar
Long, S. P. Gas exchange measurements, what can they tell us about the underlying limitations to photosynthesis? Procedures and sources of error. J. Exp. Bot. 54, 2393–2401 (2003).
Article PubMed CAS Google Scholar
Maxwell, K. & Johnson, G. N. Chlorophyll fluorescence—a practical guide. J. Exp. Bot. 51, 659–668 (2000).
Murchie, E. H. & Lawson, T. Chlorophyll fluorescence analysis: a guide to good practice and understanding some new applications. J. Exp. Bot. 64, 3983–3998 (2013).
Article PubMed CAS Google Scholar
Pfündel, E. Estimating the contribution of photosystem I to total leaf chlorophyll fluorescence. Photosynth. Res. 56, 185–195 (1998).
Pfündel, E. E., Klughammer, C., Meister, A. & Cerovic, Z. G. Deriving fluorometer-specific values of relative PSI fluorescence intensity from quenching of F0 fluorescence in leaves of Arabidopsis thaliana and Zea mays. Photosynth. Res. 114, 189–206 (2013).
Article PubMed CAS Google Scholar
Björkman, O. & Demmig, B. Photon yield of O₂ evolution and chlorophyll fluorescence characteristics at 77 K among vascular plants of diverse origins. Planta 170, 489–504 (1987).
Article PubMed Google Scholar
Heberling, J. M. & Fridley, J. D. Resource-use strategies of native and invasive plants in Eastern North American forests. New Phytol. 200, 523–533 (2013).
Article PubMed CAS Google Scholar
Feng, X. & Dietze, M. Scale dependence in the effects of leaf ecophysiological traits on photosynthesis: Bayesian parameterization of photosynthesis models. New Phytol. 200, 1132–1144 (2013).
Article PubMed CAS Google Scholar
Collatz, G. J., Ribas-Carbo, M. & Berry, J. A. Coupled photosynthesis-stomatal conductance model for leaves of C₄ plants. Aust. J. Plant Physiol. 19, 519–538 (1992).
Google Scholar
Lê, S., Josse, J. & Husson, F. FactoMineR: an R package for multivariate analysis. J. Stat. Softw. 25, 1–18 (2008).
Article Google Scholar
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Article PubMed PubMed Central CAS Google Scholar
Conway, J. R., Lex, A. & Gehlenborg, N. UpSetR: an R package for the visualization of intersecting sets and their properties. Bioinformatics 33, 2938–2940 (2017).
Article PubMed PubMed Central CAS Google Scholar
McAdam, S. A. M., Brodribb, T. J. & Ross, J. J. Shoot-derived abscisic acid promotes root growth. Plant Cell Environ. 39, 652–659 (2016).
Article PubMed CAS Google Scholar
Dautermann, O. et al. An algal enzyme required for biosynthesis of the most abundant marine carotenoids. Sci. Adv. 6, eaaw9183 (2020).
Article PubMed PubMed Central CAS Google Scholar
Kromdijk, J. et al. Improving photosynthesis and crop productivity by accelerating recovery from photoprotection. Science 354, 857–861 (2016).
Article PubMed CAS Google Scholar
Witt, H. T. Energy conversion in the functional membrane of photosynthesis. Analysis by light pulse and electric pulse methods. The central role of the electric field. Biochim. Biophys. Acta 505, 355–427 (1979).
Edgar, R., Domrachev, M. & Lash, A. E. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 30, 207–210 (2002).
Article PubMed PubMed Central CAS Google Scholar

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Acknowledgements

The research was supported by the Defense Advanced Research Projects Agency (DARPA) (HR001118C0137 to R.Z., A.E., D.N., and R.V.) and start-up funding from Donald Danforth Plant Science Center (DDPSC, to R.Z.) E.M. was supported by the William H. Danforth Fellowship in Plant Sciences and Washington University in St Louis. D.P. was supported by the Berkeley Fellowship and the NSF Graduate Research Fellowship Program Grant DGE 1752814. O.D. was supported by the Deutsche Forschungsgemeinschaft (DFG) - Project number 427925948. K.K.N. is an investigator of the Howard Hughes Medical Institute. We would like to thank Dr. Helmut Kirchhoff and Dr. Charles Pignon for helpful discussion about the TEM data and LI-6800 data, respectively. We also want to thank Drs. Blake Meyers, Sona Pandey, and Ivan Baxter for their valuable feedback about the manuscript. We acknowledge imaging support from the Advanced Bioimaging Laboratory (RRID:SCR_018951) at DDPSC and usage of the LEO 912AB Energy Filter TEM acquired through a National Science Foundation (NSF) Major Research Instrumentation grant (DBI-0116650). We also acknowledge the use of the Metabolite Profiling facility of the Bindley Bioscience Center, a core facility of the National Institute of Health-funded Indiana Clinical and Translational Sciences Institute, for assisting in the quantification of ABA levels. We appreciate the DDPSC Plant Growth Facilities for growth chamber reservation and taking care of our plants. Additionally, we thank the US Department of Energy Joint Genome Institute and the S. viridis Genome Sequencing Project for the S. viridis v2.1 genome database. DARPA approved the paper for Public Release, Distribution Unlimited.

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These authors contributed equally: Cheyenne M. Anderson, Erin M. Mattoon.

Authors and Affiliations

Donald Danforth Plant Science Center, St. Louis, MO, USA
Cheyenne M. Anderson, Erin M. Mattoon, Ningning Zhang, Eric Becker, William McHargue, Jiani Yang, Sunita Pathak, Jeffrey Berry, Maxwell Braud, Margaret Wilson, Dmitri A. Nusinow, Kirk J. Czymmek, Andrea L. Eveland & Ru Zhang
Plant and Microbial Biosciences Program, Division of Biology and Biomedical Sciences, Washington University in Saint Louis, St. Louis, MO, USA
Erin M. Mattoon
Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA
Dhruv Patel, Oliver Dautermann & Krishna K. Niyogi
Purdue Center for Plant Biology, Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN, USA
Scott A. M. McAdam
Department of Plant and Soil Sciences, University of Delaware, Newark, DE, USA
Tonantzin Tarin & Rodrigo Vargas
Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico
Tonantzin Tarin
Department of Plant Sciences, University of Cambridge, Cambridge, UK
Tom J. Avenson
Howard Hughes Medical Institute, Berkeley, CA, USA
Krishna K. Niyogi
Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
Krishna K. Niyogi

Authors

Cheyenne M. Anderson
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Erin M. Mattoon
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Ningning Zhang
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Eric Becker
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William McHargue
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Jiani Yang
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Dhruv Patel
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Oliver Dautermann
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Scott A. M. McAdam
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Tonantzin Tarin
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Sunita Pathak
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Tom J. Avenson
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Jeffrey Berry
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Maxwell Braud
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Krishna K. Niyogi
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Margaret Wilson
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Dmitri A. Nusinow
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Rodrigo Vargas
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Kirk J. Czymmek
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Andrea L. Eveland
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Ru Zhang
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Contributions

R.Z. supervised the whole project. R.Z. and C.M.A. designed and planned all the experiments. C.M.A. led the project, performed and analyzed all LI-6800 data, extracted RNA and prepared the RNA-seq library, and led sample harvest for pigment analysis. C.M.A. and E.B. grew all plants needed for the project. T.J.A. provided insight for optimized gas exchange and chlorophyll fluorescence measurements in S. viridis using the LI-6800. T.T. and R.V. performed modeling of the leaf-level gas-exchange data. N.Z., E.B., and K.J.C. performed TEM analysis. N.Z. quantified starch using assay kits. W.M. helped harvest leaf tissues and performed MultispeQ measurements. E.B. harvested leaves for ABA measurements and S.A.M.M. performed ABA analyses. D.P., O.D., and K.K.N. performed leaf pigment analysis by HPLC. M.B. and A.L.E. provided insight for RNA-seq library preparation. J.Y. and A.L.E. preprocessed RNA-seq data. E.M. led RNA-seq data analysis and generated all the heatmaps. S.P. and R.Z. identified ABA-related genes in S. viridis. E.M. identified all other genes used for the heatmaps. J.B. provided suggestions for statistical analysis. M.W. and D.A.N. helped plan, coordinate, and discuss the RNA-seq experiments. R.Z., C.M.A., and E.M. led the writing of the manuscript with the contribution of all other co-authors. All the authors discussed the results, contributed to data interpretation, and helped revise the manuscript.

Corresponding author

Correspondence to Ru Zhang.

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The authors declare no competing interests.

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Anderson, C.M., Mattoon, E.M., Zhang, N. et al. High light and temperature reduce photosynthetic efficiency through different mechanisms in the C₄ model Setaria viridis. Commun Biol 4, 1092 (2021). https://doi.org/10.1038/s42003-021-02576-2

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Received: 14 February 2021
Accepted: 03 August 2021
Published: 16 September 2021
DOI: https://doi.org/10.1038/s42003-021-02576-2

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